Libro is a
cross-platform text analysis program written in Python which
scans a whole text file (in plain text, HTML, EPUB, or ODT formats) and
ranks all used words according to frequency, performing a
quantitative analysis of the text using Shannon-Weaver
information statistic and Zipf power law function. It counts
words, chars, spaces, and syllables. Also computes readability
indexes (Gunning Fog, Coleman-Liau, Automated Readability Index
(ARI), SMOG grade, Flesch&ndashKincaid grade level and Flesch
- Zipf's law states that the
frequency of occurence of any word is approximately
inversely proportional to its rank in the frequency
table. When Zipf's law is applicable, plotting the
frequency table on a log-log scale (i.e., log(frequency)
versus log(rank order)) will typically show a linear
- Shannon-Weaver information
statistic gives a measure of the entropy (or the average
informaton content) of the text, expressed in bits.
- Gunning Fog, Coleman-Liau, Automated
Readability Index, SMOG, and Flesch-Kincaid readability
tests are designed to indicate comprehension difficulty
when reading written materials.
programs and web sites may give different numerical
results for the same text that those computed by Libro.
This occurs because they may use different formulae, but
it is more likely that they use different rules for
counting sentences or determining what is a syllable.
Indeed, results for the same text may differ in Libro
itself, if computed from source files in different
formats (eg. plain text, HTML, EPUB, ODT). However,
it is not the exact results themselves which are
important, but the qualitative interpretations which may
be derived from them, on a comparative basis.
Source code and
binary installaton packages are available from SourceForge
program is free software, made available under the GNU General Public Licence
version 3 (GPL3)
Mauro J. Cavalcanti, Rio de Janeiro, Brazil